SUMMARY:In this study the static (μ e ) and kinetic (μ d ) coefficients of friction were obtained for Pinus sylvestis L. sawn timber of Spanish origin. Friction between transverse surfaces sliding perpendicular to the grain (tangential direction) and radial surfaces sliding parallel to the grain was analyzed. A specifically designed device was used for tests, which makes it possible to apply contact pressure and measure displacements and applied loads simultaneously. Coefficients of friction between transverse surfaces (μ e = 0,24; μ d = 0,17) were about twice of the coefficients of friction between radial surfaces (μ e = 0,12; μ d = 0,08). Furthermore, these values are located within normal values of those commonly reported for softwood. The results are considered preliminary due to the small number of specimens. RESUMEN:Coeficientes de rozamiento estático y dinámico en la madera de pino silvestre (Pinus sylvestris L.), según las direcciones paralela y perpendicular a la fibra. En este estudio se determinaron los coeficientes de rozamiento, estático (μ e ) y dinámico (μ d ), en madera aserrada de Pinus sylvestris L. de procedencia española, diferenciando si se produce el contacto entre secciones de corte transversal con deslizamiento en dirección perpendicular a la fibra (en dirección tangencial), o entre secciones de corte radial con deslizamiento paralelo a la fibra. Para la realización de los ensayos se ha utilizado un dispositivo, diseñado específicamente, que posibilita la aplicación de una presión de contacto y la medición del desplazamiento y de la fuerza aplicada de manera simultánea, permitiendo la obtención de los coeficientes de rozamiento estático y dinámico. Los coeficientes de rozamiento obtenidos entre secciones transversales (μ e = 0.24; μ d = 0.17) fueron del orden del doble de los coeficientes de rozamiento entre secciones radiales (μ e = 0.12; μ d = 0.08). Además, estos valores se encuentran dentro de los valores que aparecen habitualmente en la bibliografía para madera de coníferas. Debido al escaso tamaño de la muestra los resultados se consideran preliminares.
Bending properties have been determined by mechanical testing [modulus of elasticity (MOE) and modulus of rupture (MOR)] and by means of longitudinal (L) and transverse (T) vibration nondestructive methods on 150 sawn timber pieces of Pinus radiata D. Don, with the dimensions of 80 × 120 mm cross-section and 2500 mm long, from Catalonia, Spain. The fundamental vibration frequency was measured by recording the sound produced by hitting the piece in L and T directions, and this signal was analyzed by fast Fourier transform sound analyzer. The dynamic MOE was obtained for both procedures and compared with static MOE and MOR. The notion of concentrated knot diameter ratio (CKDR) was introduced to improve the prediction of MOR. CKDR gives better results when this parameter is referred to the central portion of piece length. Both methods (L and T frequencies) have similar accuracy in prediction of mechanical properties, but the first one is simpler and has some practical advantages. The timber graded with this nondestructive method offers better results than the visual grading rules for the same output.
The non-destructive testing (NDT) of timber using the longitudinal vibration method is based on the natural frequency of wood which is in relation to its quality. In the present paper, the suitability of this tool is investigated and the results of grading 395 pieces are presented. Structural timber of Radiata pine ( Pinus radiata D. Don.), Scots pine ( Pinus sylvestris L.), and Laricio pine [ Pinus nigra ssp. salzmannii (Dunal) Franco] from Spanish sources were investigated. The specimens were tested for bending according to the European standard EN 408 (2003) and the values of strength and stiffness were compared with the results estimated by means of NDT. The vibration equipment applied permits the measurement of the longitudinal natural frequency and mass of the specimen, and then the density and the dynamic modulus of elasticity can be calculated. There is a strong relationship between the static modulus of elasticity obtained from the bending test and the dynamic modulus of elasticity obtained by the NDT technique. There is an acceptable relationship between modulus of rupture and dynamic modulus of elasticity if the visual defects (knot sizes) are taken into account. Acoustic measurements have become widely acceptable, and they have great potential for stress grading of coniferous timber.
The predictability of modulus of elasticity (MOE), modulus of rupture (MOR) and density of 120 samples of Scots pine (Pinus sylvestrisL.) were investigated using various non-destructive variables (such as time of flight of stress wave, natural frequency of longitudinal vibration, penetration depth, pullout resistance, visual grading and concentrated knot diameter ratio), and based on multivariate algorithms, applying WEKA as machine learning software. The algorithms used were: multivariate linear regression (MLR), Gaussian, Lazy, artificial neural network (ANN), Rules and decision Tree. The models were quantified based on the root-mean-square error (RMSE) and the coefficient of determination (R2). To avoid model overfitting, the modeling was built and the results validated via the so-called 10-fold cross-validation. MLR with the “greedy method” for variable selection based on the Akaike information metric (MLRak) significantly reduced the RMSE of MOR and MOE compared to univariate linear regressions (ULR). However, this reduction was not significant for density prediction. The predictability of MLRak was not improved by any other of the tested algorithms. Specifically, non-linear models, such as multilayer perceptron, did not contribute any significant improvements over linear models. Finally, MLRak models were simplified by discarding the variables that produce the lowest RMSE increment. The resulted models could be even further simplified without significant RMSE increment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.